As a mobile device and social media are vitalized in the related art, a huge number of social media data is flooding the Internet. The social media connotes a flow of a social public opinion so that various data analyses including a web trend analysis and a business intelligence (BI) and studies on social media in an information extracting field are actively being performed.
Till now, a core of the social media analysis systems is mostly an analysis of buzz progress information based on frequency information of a specific entity which is included in a keyword search word and emotional information of a sentence including the corresponding entity. Further, the individual analysis results are independent so that it is difficult to understand correlation and insight between analyzed results. Only search words which are input by users and a period to be analyzed are common between the individual analysis results.
In order to understand the insight for a specific entity using social media analysis systems of the related art, individual analysis results are independently analyzed and information on the correlation between the results is analyzed and summarized by a data analysis expert to create a report.
That is, subjectivity of an expert who performs analysis is highly likely to be reflected. This does not satisfy a demand of a user who wants to quickly analyze social media for a specific entity to understand an objective insight. Further, a report which is created by an expert suggests only a partial deflected viewpoint among various analysis viewpoints. This may not provide an insight which is obtained by understanding the analysis result from various viewpoints. That is, in order to perform analysis from various viewpoints which are demanded by individual users and understand the insight, interaction with the users is required.